The group has continued to make strides conducting imaging-genetic studies to explore basic molecular biology and genetics of human information processing in healthy controls and patients with schizophrenia. Interesting findings have emerged from these studies. 1) Using fMRI during working memory, we demonstrated that altered DLPFC connectivity is found in both patients with schizophrenia and healthy siblings and therefore is a familial and likely heritable feature of genetic risk for schizophrenia. We also discovered that this novel intermediate phenotype is independent of the well documented altered dorsolateral prefrontal cortex engagement in patients with schizophrenia and siblings (Rasetti et al. AJP 2011). These findings add to evidence that distributed network-based neurointegrative deficits manifested as disrupted network dynamics reflect genetic risk mechanisms for schizophrenia. As an illustration that some risk genes may map onto some intermediate phenotypes but not others, the group demonstrated that ZNF804A, a putative susceptibility gene for psychosis, impacts differentially on the above neuroimaging intermediate phenotypes 1) has no effect on DLPFC engagement during working memory, and 2) modulates DLPFC-HF coupling during WM (Rasetti et al. AJP 2011). 2) Tan et al. Brain 2012 explored genetic control over component working memory cortical-subcortical networks in humans, and the pharmacogenetic implications of dopamine-related genes on cognition in schizophrenic patients receiving anti-dopaminergic drugs. Using predictions from basic models of dopaminergic signaling in cortical and cortical-subcortical circuitries implicated in dissociable working memory maintenance and manipulation processes, the group examined pharmacogenetic effects on cognition in the context of anti-dopaminergic drug therapy. Using dynamic causal models of functional magnetic resonance imaging in normal subjects, we identified differentiated effects of functional polymorphisms in COMT, DRD2 and AKT1 genes on prefrontal-parietal and prefrontal-striatal circuits engaged during maintenance and manipulation, respectively. Cortical synaptic dopamine monitored by the COMT Val158Met polymorphism influenced prefrontal control of both parietal processing in working memory maintenance and striatal processing in working memory manipulation. DRD2 and AKT1 polymorphisms implicated in DRD2 signaling influenced only the prefrontal-striatal network associated with manipulation. In the context of anti-psychotic drugs, the DRD2 and AKT1 polymorphisms altered dose-response effects of anti-psychotic drugs on cognition in schizophrenia. These findings suggest that genetic modulation of DRD2-AKT1-related prefrontal-subcortical circuits could, at least in part, influence cognitive dysfunction in psychosis and its treatment. 3) Another study, Marenco et al. Neuropsychopharmacology 2012, studied measures of anatomical connectivity between the thalamus and lateral prefrontal cortex (LPFC) in patients with schizophrenia and controls, and assessed their functional implications. Thalamocortical connectivity was measured with diffusion tensor imaging (DTI) and probabilistic tractography. The relationship between thalamocortical connectivity and prefrontal cortical BOLD functional activity and behavioral performance during working memory was also assessed. Compared with controls, patients with schizophrenia showed reduced total connectivity of the thalamus to only 1 of 6 cortical regions, namely the LPFC. The size of the thalamic region with at least 25% of model fibers reaching the LPFC was also reduced in patients compared with controls. The total thalamocortical connectivity to the LPFC predicted working memory task performance and also correlated with LPFC BOLD activation. The correlation with BOLD activation was accentuated in patients compared with controls in the ventral LPFC. These results suggest that thalamocortical connectivity to the LPFC is altered in schizophrenia with functional consequences on working memory processing in LPFC. The group has also continued to make strides in the field of cognitive aging. Interesting findings have emerged from these studies as well. 1) Using a novel data driven analysis approach with parallel independent component analysis, we explored the effect of normal aging on the effect of aging on networks common to multiple brain processes (e.g. working memory and episodic memory cognitive functions that have been shown to decline with age). The results from this study suggested that cognitive aging is associated with alteration in connectivity within prefrontoparietal networks that is not memory domain specific. These findings are in line with the dedifferentiation hypothesis of neurocognitive aging, and suggest decreased specialization of the brain networks supporting different memory networks with advancing age (Sambataro et al.Eur J Neurosci 2012). 2) The group also explored the neurobiology underlying age-related changes in working memory updating using fMRI with healthy subjects from across the adult age spectrum. The study results indicate that older age is associated with poorer performance, reduced meso-cortico-striatal activation, and reduced functional coupling between the caudate and the VLPFC during working memory updating. Based on prior evidence that normal aging is associated with decline in executive functions along with a progressive decline of neurotransmitter systems including dopamine (DA), these results are consistent with computational models of executive cognition and DA-mediated age-related decline. Given the known relationship between aging and DA system decline, these findings add to the literature on the neurobiology of the central executive and of age-related cognitive decline (Podell et al. Neuroimage 2012).